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DBMS > Dragonfly vs. Google Cloud Datastore vs. Hawkular Metrics vs. Prometheus vs. STSdb

System Properties Comparison Dragonfly vs. Google Cloud Datastore vs. Hawkular Metrics vs. Prometheus vs. STSdb

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPrometheus  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open-source Time Series DBMS and monitoring systemKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeDocument storeTime Series DBMSTime Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorewww.hawkular.orgprometheus.iogithub.com/­STSSoft/­STSdb4
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guideprometheus.io/­docs
DeveloperDragonflyDB team and community contributorsGoogleCommunity supported by Red HatSTS Soft SC
Initial release20232008201420152011
Current release1.0, March 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaGoC#
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
Windows
Windows
Data schemescheme-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereyesNumeric data onlyyes infoprimitive types and user defined types (classes)
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono infoImport of XML data possible
Secondary indexesnoyesnonono
SQL infoSupport of SQLnoSQL-like query language (GQL)nonono
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTRESTful HTTP/JSON API.NET Client API
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresLuausing Google App Enginenonono
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
none
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonono
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonono

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More resources
DragonflyGoogle Cloud DatastoreHawkular MetricsPrometheusSTSdb
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